evokingkongbist.java~

来自「Java遗传算法库」· JAVA~ 代码 · 共 745 行 · 第 1/4 页

        String blifFN = "/home/mmg20/eh/benchmarks/bw.blif";
        String sisQFN = "/home/mmg20/eh/benchmarks/bw.sout";
        String dirName = "BWL";
        String descr = "Locked Benchmark: BW (209 gates)";
        int bestHD = 1677;
        addCombBLIFBenchmark( blifFN, sisQFN, dirName, descr, bestHD );
    }
    
    protected static void addCombBLIFBenchmark( String blifFileName, String sisOutputFileName, String dirName, String descr, int bestIndID ) throws IOException
    {
        final double T_SETUP = 0.95;
        final int INPUT_SAMPLE_SEP = 30;
        // D -  Circuit Structure Properties
         final int LUT_INPUTS = 2;
        
        // B - BENCHMARK STUFF
        CombinationalBLIFExperiment experiment = new CombinationalBLIFExperiment( blifFileName, T_SETUP );
        final int E_LINES = 1;
        final boolean FPGA = false;
        final boolean VOTER = true;
        SisOutputReader sor = new SisOutputReader( new File( sisOutputFileName ), E_LINES, LUT_INPUTS, FPGA, VOTER );
        FullOrderGenotype seed = new FullOrderGenotype ( sor.getGenotype() );
        int bitsPerVar = sor.getBitsPerVar();
        int usedEls = sor.getTotalEls();
        SingleFaultModel faultModel = new SingleFullFaultModel( usedEls );
        
        // A - Genetic Algorithms Properties
        // Standard
         final int POP_SIZE = 32;
         final int GENOTYPE_MUT = 1;
         final int NUM_OF_ELITES = 2;

        // M - Log Properties
         int DUMP_POP_EVERY = 1000;
        
        // D - DEPLOYMENT set up
        ElementDelayModel delayModel = new CoinDelayModel( );
        //ElementDelayModel delayModel = new GaussianDelayModel( 0.3, 0.3 );
        CircuitMapping circuitMapping = new LUTAbsoluteMapping( experiment.getNumOfInputs(), experiment.getNumOfOutputs() + E_LINES, bitsPerVar, LUT_INPUTS, delayModel );
        SimulatorFaultyCircuit circuit = new SimulatorFaultyCircuit( circuitMapping );
        SimulatorDeployment deployment = new SimulatorDeployment( circuit );

        // A - Genetic Operators Set up
        int nrAddUnits = ( 1 << bitsPerVar ) - experiment.getNumOfInputs();
        int lutSize = 1 << LUT_INPUTS;
        int blockSize = lutSize + LUT_INPUTS * bitsPerVar;
        int genotypeLength = nrAddUnits * blockSize;

        Genotype[] seeds = new Genotype[ POP_SIZE ];
        //seeds[ 0 ] = seed;
        for( int pl = 0; pl < POP_SIZE; pl++ )
        {
            seeds[ pl ] = ( FullOrderGenotype ) seed.clone();
            for( int bl = usedEls * blockSize; bl < seeds[ pl ].length(); bl++ )
            {
                if( Math.random() < 0.5 )
                {
                    seeds[ pl ].set( bl );
                }
            }
        }
        
        int fixedAlignments = usedEls;
        int howManyBunches = 1;
        //GeneticOperator m = new SAGAMutator( 1, genotypeLength / 50, 0, fixedAlignments * blockSize, -1 );
        ExactGenotypeMutator m = new ExactGenotypeMutator( ( int ) ( genotypeLength / 500 ) + 1 ); // For real biggies
        m.setRange( fixedAlignments * blockSize, -1 );
        GeneticOperator spxo = new SinglePointXOver();
        GeneticOperator bmin0 = new BunchMutator( bitsPerVar, howManyBunches, blockSize, lutSize, fixedAlignments );
        GeneticOperator bmin1 = new BunchMutator( bitsPerVar, howManyBunches, blockSize, lutSize + bitsPerVar, fixedAlignments );
        GeneticOperator bc = new BlockCopy ( blockSize, blockSize, 0, fixedAlignments );
        GeneticOperator[] geneticOps = { m, spxo, bmin0, bmin1, bc };
        double[] opsProbs = { 0.2, 0.3, 0.1, 0.1, 0.2 };
        Selector selector = new RankSelector(  );
        Evolver evolver = new StandardEvolver( POP_SIZE, genotypeLength, geneticOps, opsProbs, selector, NUM_OF_ELITES, seeds );
        
        PopulationLogReader.fullOrderGenotypes = true;
        int nrEvals = 1;
        int eSize = 15;
        boolean overdetecting = true;
        CircuitPainterObject painter = new CircuitPainterObject( new CircuitPainter(), new LUTAbsoluteMapping( experiment.getNumOfInputs(), experiment.getNumOfOutputs() + E_LINES, bitsPerVar, LUT_INPUTS, new ConstantDelayModel( 0 ) ) ); 
        BISTPIM inIm = new BISTPIM( evolver, deployment, circuit, experiment, faultModel, eSize, overdetecting, INPUT_SAMPLE_SEP, painter );
        int[] numProps = { 2 };
        InteractionModel noisyIM = new NoisyPIM( inIm, deployment, experiment, numProps, nrEvals );
        double maxSize = nrAddUnits;
        InteractionModel interactionModel = new CircuitParsimonyPIM( noisyIM, circuit, maxSize );
        Monica monica = new Monica( interactionModel, DUMP_POP_EVERY, java.lang.Integer.MAX_VALUE );
        painter.setEvoTask( monica );
        monica.setName( dirName );
        taskQ.add( monica );
        taskQNames.add( dirName );
        taskQDescr.add( descr );
        taskQBestIndID.add( new Integer( bestIndID ) );
        ControlLib.writeGNUPlotScript( dirName, logDir, logFileName, 3, false );        
        ControlLib.writeWebGraphDaemon( dirName, logDir, logFileName, 3, false, new File(".").getCanonicalPath() + File.separator );
        int avgSize = ( int )( usedEls * 1.45 );
        int effort = nrEvals * INPUT_SAMPLE_SEP * avgSize * avgSize * ( 1 << experiment.getNumOfInputs() );
        taskQEffort.add( new Integer( effort ) );        
    }

    protected static void addCombBLIFBenchmarkNoLocking( String blifFileName, String sisOutputFileName, String dirName, String descr, int bestIndID ) throws IOException
    {
        final double T_SETUP = 0.45;
        final int INPUT_SAMPLE_SEP = 100;
        // D -  Circuit Structure Properties
         final int LUT_INPUTS = 2;
        
        // B - BENCHMARK STUFF
        CombinationalBLIFExperiment experiment = new CombinationalBLIFExperiment( blifFileName, T_SETUP );
        final int E_LINES = 1;
        final boolean FPGA = false;
        final boolean VOTER = true;
        SisOutputReader sor = new SisOutputReader( new File( sisOutputFileName ), E_LINES, LUT_INPUTS, FPGA, VOTER );
        FullOrderGenotype seed = new FullOrderGenotype ( sor.getGenotype() );
        int bitsPerVar = sor.getBitsPerVar();   
        int usedEls = sor.getTotalEls();        
        // A - Genetic Algorithms Properties
        // Standard
        final int POP_SIZE = 32;
        final int GENOTYPE_MUT = 1;
        final int NUM_OF_ELITES = 2;
        // M - Log Properties
        int DUMP_POP_EVERY = 50;
        // D - DEPLOYMENT set up
        ElementDelayModel delayModel = new CoinDelayModel( );
        //ElementDelayModel delayModel = new GaussianDelayModel( 0.3, 0.3 );
        CircuitMapping circuitMapping = new LUTAbsoluteMapping( experiment.getNumOfInputs(), experiment.getNumOfOutputs() + E_LINES, bitsPerVar, LUT_INPUTS, delayModel );
        SimulatorFaultyCircuit circuit = new SimulatorFaultyCircuit( circuitMapping );
        SimulatorDeployment deployment = new SimulatorDeployment( circuit );
        SingleFaultModel faultModel = new SingleUsedFaultModel( circuit, experiment.getNumOfOutputs() );
        
        // A - Genetic Operators Set up
        int nrAddUnits = ( 1 << bitsPerVar ) - experiment.getNumOfInputs();
        int lutSize = 1 << LUT_INPUTS;
        int blockSize = lutSize + LUT_INPUTS * bitsPerVar;
        int genotypeLength = nrAddUnits * blockSize;

        Genotype[] seeds = new Genotype[ POP_SIZE ];
        seeds[ 0 ] = seed;
        for( int pl = 1; pl < POP_SIZE; pl++ )
        {
            seeds[ pl ] = ( FullOrderGenotype ) seed.clone();
            for( int bl = 0; bl < seeds[ pl ].length(); bl++ )
            {
                if( Math.random() < 0.5 )
                {
                    seeds[ pl ].set( bl );
                }
            }
        }
        int howManyBunches = 1;
        GeneticOperator m = new SAGAMutator( 1, genotypeLength / 100, 0 );
        //ExactGenotypeMutator m = new ExactGenotypeMutator( ( int ) ( genotypeLength / 500 ) + 1 ); // for biggies
        GeneticOperator spxo = new SinglePointXOver();
        GeneticOperator bmin0 = new BunchMutator( bitsPerVar, howManyBunches, blockSize, lutSize );
        GeneticOperator bmin1 = new BunchMutator( bitsPerVar, howManyBunches, blockSize, lutSize + bitsPerVar );
        GeneticOperator bc = new BlockCopy ( blockSize, blockSize, 0 );        
        GeneticOperator[] geneticOps = { m, spxo, bmin0, bmin1, bc };
        double[] opsProbs = { 0.2, 0.2, 0.2, 0.2, 0.2 };
        Selector selector = new RankSelector(  );
        Evolver evolver = new StandardEvolver( POP_SIZE, genotypeLength, geneticOps, opsProbs, selector, NUM_OF_ELITES, seeds );
        
        PopulationLogReader.fullOrderGenotypes = true;
        int nrEvals = 1;
        int eSize = 30;
        boolean overdetecting = true;
        CircuitPainterObject painter = new CircuitPainterObject( new CircuitPainter(), new LUTAbsoluteMapping( experiment.getNumOfInputs(), experiment.getNumOfOutputs() + E_LINES, bitsPerVar, LUT_INPUTS, new ConstantDelayModel( 0 ) ) ); 
        BISTPIM inIm = new BISTPIM( evolver, deployment, circuit, experiment, faultModel, eSize, overdetecting, INPUT_SAMPLE_SEP, painter );
        int[] numProps = { 2 };
        InteractionModel noisyIM = new NoisyPIM( inIm, deployment, experiment, numProps, nrEvals );
        double maxSize = nrAddUnits;        
        InteractionModel interactionModel = new CircuitParsimonyPIM( noisyIM, circuit, maxSize );
        Monica monica = new Monica( interactionModel, DUMP_POP_EVERY, java.lang.Integer.MAX_VALUE );
        painter.setEvoTask( monica );
        monica.setName( dirName );
        taskQ.add( monica );
        taskQNames.add( dirName );
        taskQDescr.add( descr );
        taskQBestIndID.add( new Integer( bestIndID ) );
        ControlLib.writeGNUPlotScript( dirName, logDir, logFileName, 3, false );
        ControlLib.writeWebGraphDaemon( dirName, logDir, logFileName, 3, false, new File(".").getCanonicalPath() + File.separator );
    }    
}